A search for 95 GHz class I methanol masers in molecular outflows

We have observed a sample of 288 molecular outflow sources including 123 high-mass and 165 low-mass sources to search for class I methanol masers at 95 GHz transition and to investigate relationship between outflow characteristics and class I methanol maser emission with the PMO-13.7m radio telescope. Our survey detected 62 sources with 95 GHz methanol masers above 3$\sigma$ detection limit, which include 47 high-mass sources and 15 low-mass sources. Therefore the detection rate is 38% for high-mass outflow sources and 9% for low-mass outflow sources, suggesting that class I methanol maser is relatively easily excited in high-mass sources. There are 37 newly detected 95 GHz methanol masers (including 27 high-mass and 10 low-mass sources), 19 of which are newly identified (i.e. first identification) class I methanol masers (including 13 high-mass and 6 low-mass sources). Statistical analysis for the distributions of maser detections with the outflow parameters reveals that the maser detection efficiency increases with outflow properties (e.g. mass, momentum, kinetic energy and mechanical luminosity of outflows etc.). Systematic investigations of relationships between the intrinsic luminosity of methanol maser and the outflow properties (including mass, momentum, kinetic energy, bolometric luminosity and mass loss rate of central stellar sources) indicate a positive correlations. This further supports that class I methanol masers are collisionally pumped and associated with shocks, where outflows interact with the surrounding ambient medium.Comment: 32 pages, 5 figures, accepted by Ap

Pain and Efficacy Rating of a Microprocessor-Controlled Metered Injection System for Local Anaesthesia in Minor Hand Surgery

Purpose. Little attention has been given to syringe design and local anaesthetic administration methods. A microprocessor-controlled anaesthetic delivery device has become available that may minimize discomfort during injection. The purpose of this study was to document the pain experience associated with the use of this system and to compare it with use of a conventional syringe. Methods. A prospective, randomized clinical trial was designed. 40 patients undergoing carpal tunnel release were block randomized according to sex into a two groups: a traditional syringe group and a microprocessor-controlled device group. The primary outcome measure was surgical pain and local anaesthetic administration pain. Secondary outcomes included volume of anaesthetic used and injection time. Results. Analysis showed that equivalent anaesthesia was achieved in the microprocessor-controlled group despite using a significantly lower volume of local anaesthetic (P = .0002). This same group, however, has significantly longer injection times (P < .0001). Pain during the injection process or during surgery was not different between the two groups. Conclusions. This RCT comparing traditional and microprocessor controlled methods of administering local anaesthetic showed similar levels of discomfort in both groups. While the microprocessor-controlled group used less volume, the total time for the administration was significantly greater

The effect of prestressing force on natural frequencies of concrete beams - A numerical validation of existing experiments by modelling shrinkage crack closure

This paper investigates the effect of prestressing force on the natural frequencies of reinforced concrete beams. From a pure theoretical point of view, such effects in different prestressing conditions appear to involve no ambiguity; however, in practice contradictory observations have been reported in existing research publications. Theoretical studies showed that natural frequencies would be decreasing or unchanged in different scenarios. On the other hand, some experiments that were conducted on prestressed concrete beams indicated an increasing trend of the natural frequencies with the prestressing force. This paper is aimed to provide a systematic explanation of the reasons causing the discrepancies and propose a coherent framework for the prediction of the natural frequencies under a prestressed condition. Numerical simulations using finite element model are carried out to simulate the influence of prestressing force on natural frequencies with the existence of the shrinkage cracks. The results demonstrate that such shrinkage-type cracks inside the concrete indeed tend to close when the prestressing force is applied, and this in turn increases the bending stiffness and consequently results in an increase of the natural frequencies of the beams.MOE (Min. of Education, S’pore)Accepted versio

Hexaaqua­cobalt(II) bis­{[N-(4-meth­oxy-2-oxidobenzyl­idene)glycyl­glycinato]copper(II)} hexa­hydrate

In the crystal structure of the title compound, [Co(H2O)6][Cu(C12H11N2O5)]2·6H2O, the CoII atom is located on an inversion center and coordinated by six water mol­ecules in a slightly distorted octa­hedral geometry. The CuII atom is chelated by the Schiff base ligand in a distorted CuN2O2 square-planar geometry. An extensive O—H⋯O hydrogen-bonding network is present in the crystal structure

Topological surface electronic states in candidate nodal-line semimetal CaAgAs

We investigate systematically the bulk and surface electronic structure of the candidate nodal-line semimetal CaAgAs by angle resolved photoemission spectroscopy and density functional calculations. We observed a metallic, linear, non-$k_z$-dispersive surface band that coincides with the high-binding-energy part of the theoretical topological surface state, proving the topological nontriviality of the system. An overall downshift of the experimental Fermi level points to a rigid-band-like $p$-doping of the samples, due possibly to Ag vacancies in the as-grown crystals.Comment: 6 pages, 5 figure

Single-Image-Based Deep Learning for Segmentation of Early Esophageal Cancer Lesions

Accurate segmentation of lesions is crucial for diagnosis and treatment of early esophageal cancer (EEC). However, neither traditional nor deep learning-based methods up to today can meet the clinical requirements, with the mean Dice score - the most important metric in medical image analysis - hardly exceeding 0.75. In this paper, we present a novel deep learning approach for segmenting EEC lesions. Our approach stands out for its uniqueness, as it relies solely on a single image coming from one patient, forming the so-called "You-Only-Have-One" (YOHO) framework. On one hand, this "one-image-one-network" learning ensures complete patient privacy as it does not use any images from other patients as the training data. On the other hand, it avoids nearly all generalization-related problems since each trained network is applied only to the input image itself. In particular, we can push the training to "over-fitting" as much as possible to increase the segmentation accuracy. Our technical details include an interaction with clinical physicians to utilize their expertise, a geometry-based rendering of a single lesion image to generate the training set (the \emph{biggest} novelty), and an edge-enhanced UNet. We have evaluated YOHO over an EEC data-set created by ourselves and achieved a mean Dice score of 0.888, which represents a significant advance toward clinical applications

High Throughput Sequencing Identifies MicroRNAs Mediating α-Synuclein Toxicity by Targeting Neuroactive-Ligand Receptor Interaction Pathway in Early Stage of Drosophila Parkinson\u27s Disease Model.

Parkinson\u27s disease (PD) is a prevalent neurodegenerative disorder with pathological features including death of dopaminergic neurons in the substantia nigra and intraneuronal accumulations of Lewy bodies. As the main component of Lewy bodies, α-synuclein is implicated in PD pathogenesis by aggregation into insoluble filaments. However, the detailed mechanisms underlying α-synuclein induced neurotoxicity in PD are still elusive. MicroRNAs are ~20nt small RNA molecules that fine-tune gene expression at posttranscriptional level. A plethora of miRNAs have been found to be dysregulated in the brain and blood cells of PD patients. Nevertheless, the detailed mechanisms and their in vivo functions in PD still need further investigation. By using Drosophila PD model expressing α-synuclein A30P, we examined brain miRNA expression with high-throughput small RNA sequencing technology. We found that five miRNAs (dme-miR-133-3p, dme-miR-137-3p, dme-miR-13b-3p, dme-miR-932-5p, dme-miR-1008-5p) were upregulated in PD flies. Among them, miR-13b, miR-133, miR-137 are brain enriched and highly conserved from Drosophila to humans. KEGG pathway analysis using DIANA miR-Path demonstrated that neuroactive-ligand receptor interaction pathway was most likely affected by these miRNAs. Interestingly, miR-137 was predicted to regulate most of the identified targets in this pathway, including dopamine receptor (DopR, D2R), γ-aminobutyric acid (GABA) receptor (GABA-B-R1, GABA-B-R3) and N-methyl-D-aspartate (NMDA) receptor (Nmdar2). The validation experiments showed that the expression of miR-137 and its targets was negatively correlated in PD flies. Further experiments using luciferase reporter assay confirmed that miR-137 could act on specific sites in 3\u27 UTR region of D2R, Nmdar2 and GABA-B-R3, which downregulated significantly in PD flies. Collectively, our findings indicate that α-synuclein could induce the dysregulation of miRNAs, which target neuroactive ligand-receptor interaction pathway in vivo. We believe it will help us further understand the contribution of miRNAs to α-synuclein neurotoxicity and provide new insights into the pathogenesis driving PD